Message-ID: <AANLkTikuejpXG_1F5_s9DL1VOxnYmp3pw0G7xc4mOAiP@mail.gmail.com>
Date: 2011-01-12T04:35:48Z
From: Joshua Ulrich
Subject: Aggragating subsets of data in larger vector with sapply
In-Reply-To: <1294618238401-3206445.post@n4.nabble.com>
Hi Chris,
This seems to work on the sample data you provided.
FUN <- function(x) {
x <- xts(as.numeric(x),index(x))
period.apply(x, endpoints(x,"secs"), sum)
}
lapply(split.default(xSym$Size,xSym$Direction), FUN)
Best,
--
Joshua Ulrich ?| ?FOSS Trading: www.fosstrading.com
On Sun, Jan 9, 2011 at 6:10 PM, rivercode <aquanyc at gmail.com> wrote:
>
>
> Have 40,000 rows of buy/sell trade data and am trying to add up the buys for
> each second, the code works but it is very slow. ?Any suggestions how to
> improve the sapply function ?
>
> secEP = endpoints(xSym$Direction, "secs") ?# vector of last second on an XTS
> timeseries object with multiple entries for each second.
> d = xSym$Direction
> s = xSym$Size
> buySize = sapply(1:(length(secEP)-1), function(y) {
> ? ? ? ?i = ?(secEP[y]+ 1):secEP[y+1]; # index of vectors between each secEP
> ? ? ? ?return(sum(as.numeric(s[i][d[i] == "buy"])));
> } )
>
> Object details:
>
> secEP = numeric Vector of one second Endpoints in xSym$Direction.
>
>> head(xSym$Direction)
> ? ? ? ? ? ? ? ? ? ?Direction
> 2011-01-05 09:30:00 "unkn"
> 2011-01-05 09:30:02 "sell"
> 2011-01-05 09:30:02 "buy"
> 2011-01-05 09:30:04 "buy"
> 2011-01-05 09:30:04 "buy"
> 2011-01-05 09:30:04 "buy"
>
>> head(xSym$Size)
> ? ? ? ? ? ? ? ? ? ?Size
> 2011-01-05 09:30:00 " 865"
> 2011-01-05 09:30:02 " 100"
> 2011-01-05 09:30:02 " 100"
> 2011-01-05 09:30:04 " 100"
> 2011-01-05 09:30:04 " 100"
> 2011-01-05 09:30:04 " ?41"
>
> Thanks,
> Chris
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Aggragating-subsets-of-data-in-larger-vector-with-sapply-tp3206445p3206445.html
> Sent from the R help mailing list archive at Nabble.com.
>
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